期刊
ENGINEERING OPTIMIZATION
卷 50, 期 6, 页码 1016-1040出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/0305215X.2017.1367391
关键词
Multi-fidelity optimization; efficient global optimization; kriging method; expected improvement; helicopter blade design
资金
- Grants-in-Aid for Scientific Research [15K05797] Funding Source: KAKEN
A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.
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